Protein-protein interaction network

Gene expression profiling of epithelial ovarian cancer reveals key genes and pathways associated with chemotherapy resistance

M. Zhang, Luo, S. C., Zhang, M., Luo, S. C., Zhang, M., and Luo, S. C., Gene expression profiling of epithelial ovarian cancer reveals key genes and pathways associated with chemotherapy resistance, vol. 15, p. -, 2016.

The aim of this study is to analyze gene expression data to identify key genes and pathways associated with resistance to platinum-based chemotherapy in epithelial ovarian cancer (EOC) and to improve clinical treatment strategies. The gene expression data set was downloaded from Gene Expression Omnibus and included 12 chemotherapy-resistant EOC samples and 16 chemotherapy-sensitive EOC samples. A differential analysis was performed to screen out differentially expressed genes (DEGs).

Critical genes in head and neck squamous cell carcinoma revealed by bioinformatic analysis of gene expression data

B. Wang, Wang, T., Cao, X. L., and Li, Y., Critical genes in head and neck squamous cell carcinoma revealed by bioinformatic analysis of gene expression data, vol. 14, pp. 17406-17415, 2015.

In this study, bioinformatic analysis of gene expression data of head and neck squamous cell carcinoma (HNSCC) was performed to identify critical genes. Gene expression data of HNSCC were downloaded from the Cancer Genome Atlas (TCGA) and differentially expressed genes were determined through significance analysis of microarrays. Protein-protein interaction networks were constructed and used to identify hub genes. Functional enrichment analysis was performed with DAVID. Relevant microRNAs, transcription factors, and small molecule drugs were predicted by the Fisher exact test.

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